MVMRmode: Introducing an R package for plurality valid estimators for multivariable Mendelian randomisation.

BACKGROUND: Mendelian randomisation (MR) is the use of genetic variants as instrumental variables. Mode-based estimators (MBE) are one of the most popular types of estimators used in univariable-MR studies and is often used as a sensitivity analysis for pleiotropy. However, because there are no plurality valid regression estimators, modal estimators for multivariable-MR have been under-explored. METHODS: We use the residual framework for multivariable-MR to introduce two multivariable modal estimators: multivariable-MBE, which uses IVW to create residuals fed into a traditional plurality valid estimator, and an estimator which instead has the residuals fed into the contamination mixture method (CM), multivariable-CM. We then use Monte-Carlo simulations to explore the performance of these estimators when compared to existing ones and re-analyse the data used by Grant and Burgess (2021) looking at the causal effect of intelligence, education, and household income on Alzheimer's disease as an applied example. RESULTS: In our simulation, we found that multivariable-MBE was generally too variable to be much use. Multivariable-CM produced more precise estimates on the other hand. Multivariable-CM performed better than MR-Egger in almost all settings, and Weighted Median under balanced pleiotropy. However, it underperformed Weighted Median when there was a moderate amount of directional pleiotropy. Our re-analysis supported the conclusion of Grant and Burgess (2021), that intelligence had a protective effect on Alzheimer's disease, while education, and household income do not have a causal effect. CONCLUSIONS: Here we introduced two, non-regression-based, plurality valid estimators for multivariable MR. Of these, "multivariable-CM" which uses IVW to create residuals fed into a contamination-mixture model, performed the best. This estimator uses a plurality of variants valid assumption, and appears to provide precise and unbiased estimates in the presence of balanced pleiotropy and small amounts of directional pleiotropy.

Mediating Factors in the Association of Maternal Educational Level With Pregnancy Outcomes: A Mendelian Randomization Study.

Importance: Lower educational attainment is associated with increased risk of adverse pregnancy outcomes, but it is unclear which pathways mediate this association. Objective: To investigate the association between educational attainment and pregnancy outcomes and the proportion of this association that is mediated through modifiable cardiometabolic risk factors. Design, Setting, and Participants: In this 2-sample mendelian randomization (MR) cohort study, uncorrelated (R2 < 0.01) single-nucleotide variants (formerly single-nucleotide polymorphisms) associated with the exposure (P < 5 × 10-8) and mediators and genetic associations with the pregnancy outcomes from genome-wide association studies were extracted. All participants were of European ancestry and were largely from Finland, Iceland, the United Kingdom, or the US. The inverse variance-weighted method was used in the main analysis, and the weighted median, weighted mode, and MR Egger regression were used in sensitivity analyses. In mediation analyses, the direct effect of educational attainment estimated in multivariable MR was compared with the total effect estimated in the main univariable MR analysis. Data were extracted between December 1, 2022, and April 30, 2023. Exposure: Genetically estimated educational attainment. The mediators considered were genetically estimated type 2 diabetes, body mass index, smoking, high-density lipoprotein cholesterol level, and systolic blood pressure. Main Outcomes and Measures: Ectopic pregnancy, hyperemesis gravidarum, gestational diabetes, preeclampsia, preterm birth, and offspring birth weight. Results: The analyses included 3 037 499 individuals with data on educational attainment, and those included in studies on pregnancy outcomes ranged from 141 014 for ectopic pregnancy to 270 002 with data on offspring birth weight. Each SD increase in genetically estimated educational attainment (ie, 3.4 years) was associated with an increased birth weight of 42 (95% CI, 28-56) g and an odds ratio ranging from 0.53 (95% CI, 0.46-0.60) for ectopic pregnancy to 0.81 (95% CI, 0.71-0.93) for preeclampsia. The combined proportion of the association that was mediated by the 5 cardiometabolic risk factors ranged from -17% (95% CI, -46% to 26%) for hyperemesis gravidarum to 78% (95% CI, 10%-208%) for preeclampsia. Sensitivity analyses accounting for pleiotropy were consistent with the main analyses. Conclusions and Relevance: In this MR cohort study, intervening for type 2 diabetes, body mass index, smoking, high-density lipoprotein cholesterol level, and systolic blood pressure may lead to reductions in several adverse pregnancy outcomes associated with lower levels of education. Such public health interventions would serve to reduce health disparities attributable to social inequalities.

Uncovering associations between pre-existing conditions and COVID-19 Severity: A polygenic risk score approach across three large biobanks.

OBJECTIVE: To overcome the limitations associated with the collection and curation of COVID-19 outcome data in biobanks, this study proposes the use of polygenic risk scores (PRS) as reliable proxies of COVID-19 severity across three large biobanks: the Michigan Genomics Initiative (MGI), UK Biobank (UKB), and NIH All of Us. The goal is to identify associations between pre-existing conditions and COVID-19 severity. METHODS: Drawing on a sample of more than 500,000 individuals from the three biobanks, we conducted a phenome-wide association study (PheWAS) to identify associations between a PRS for COVID-19 severity, derived from a genome-wide association study on COVID-19 hospitalization, and clinical pre-existing, pre-pandemic phenotypes. We performed cohort-specific PRS PheWAS and a subsequent fixed-effects meta-analysis. RESULTS: The current study uncovered 23 pre-existing conditions significantly associated with the COVID-19 severity PRS in cohort-specific analyses, of which 21 were observed in the UKB cohort and two in the MGI cohort. The meta-analysis yielded 27 significant phenotypes predominantly related to obesity, metabolic disorders, and cardiovascular conditions. After adjusting for body mass index, several clinical phenotypes, such as hypercholesterolemia and gastrointestinal disorders, remained associated with an increased risk of hospitalization following COVID-19 infection. CONCLUSION: By employing PRS as a proxy for COVID-19 severity, we corroborated known risk factors and identified novel associations between pre-existing clinical phenotypes and COVID-19 severity. Our study highlights the potential value of using PRS when actual outcome data may be limited or inadequate for robust analyses.

Polygenic risk scores in cardiovascular risk prediction: A cohort study and modelling analyses.

BACKGROUND: Polygenic risk scores (PRSs) can stratify populations into cardiovascular disease (CVD) risk groups. We aimed to quantify the potential advantage of adding information on PRSs to conventional risk factors in the primary prevention of CVD. METHODS AND FINDINGS: Using data from UK Biobank on 306,654 individuals without a history of CVD and not on lipid-lowering treatments (mean age [SD]: 56.0 [8.0] years; females: 57%; median follow-up: 8.1 years), we calculated measures of risk discrimination and reclassification upon addition of PRSs to risk factors in a conventional risk prediction model (i.e., age, sex, systolic blood pressure, smoking status, history of diabetes, and total and high-density lipoprotein cholesterol). We then modelled the implications of initiating guideline-recommended statin therapy in a primary care setting using incidence rates from 2.1 million individuals from the Clinical Practice Research Datalink. The C-index, a measure of risk discrimination, was 0.710 (95% CI 0.703-0.717) for a CVD prediction model containing conventional risk predictors alone. Addition of information on PRSs increased the C-index by 0.012 (95% CI 0.009-0.015), and resulted in continuous net reclassification improvements of about 10% and 12% in cases and non-cases, respectively. If a PRS were assessed in the entire UK primary care population aged 40-75 years, assuming that statin therapy would be initiated in accordance with the UK National Institute for Health and Care Excellence guidelines (i.e., for persons with a predicted risk of ≥10% and for those with certain other risk factors, such as diabetes, irrespective of their 10-year predicted risk), then it could help prevent 1 additional CVD event for approximately every 5,750 individuals screened. By contrast, targeted assessment only among people at intermediate (i.e., 5% to <10%) 10-year CVD risk could help prevent 1 additional CVD event for approximately every 340 individuals screened. Such a targeted strategy could help prevent 7% more CVD events than conventional risk prediction alone. Potential gains afforded by assessment of PRSs on top of conventional risk factors would be about 1.5-fold greater than those provided by assessment of C-reactive protein, a plasma biomarker included in some risk prediction guidelines. Potential limitations of this study include its restriction to European ancestry participants and a lack of health economic evaluation. CONCLUSIONS: Our results suggest that addition of PRSs to conventional risk factors can modestly enhance prediction of first-onset CVD and could translate into population health benefits if used at scale.

Natriuretic peptides and integrated risk assessment for cardiovascular disease: an individual-participant-data meta-analysis.

BACKGROUND: Guidelines for primary prevention of cardiovascular diseases focus on prediction of coronary heart disease and stroke. We assessed whether or not measurement of N-terminal-pro-B-type natriuretic peptide (NT-proBNP) concentration could enable a more integrated approach than at present by predicting heart failure and enhancing coronary heart disease and stroke risk assessment. METHODS: In this individual-participant-data meta-analysis, we generated and harmonised individual-participant data from relevant prospective studies via both de-novo NT-proBNP concentration measurement of stored samples and collection of data from studies identified through a systematic search of the literature (PubMed, Scientific Citation Index Expanded, and Embase) for articles published up to Sept 4, 2014, using search terms related to natriuretic peptide family members and the primary outcomes, with no language restrictions. We calculated risk ratios and measures of risk discrimination and reclassification across predicted 10 year risk categories (ie, <5%, 5% to <7·5%, and ≥7·5%), adding assessment of NT-proBNP concentration to that of conventional risk factors (ie, age, sex, smoking status, systolic blood pressure, history of diabetes, and total and HDL cholesterol concentrations). Primary outcomes were the combination of coronary heart disease and stroke, and the combination of coronary heart disease, stroke, and heart failure. FINDINGS: We recorded 5500 coronary heart disease, 4002 stroke, and 2212 heart failure outcomes among 95 617 participants without a history of cardiovascular disease in 40 prospective studies. Risk ratios (for a comparison of the top third vs bottom third of NT-proBNP concentrations, adjusted for conventional risk factors) were 1·76 (95% CI 1·56-1·98) for the combination of coronary heart disease and stroke and 2·00 (1·77-2·26) for the combination of coronary heart disease, stroke, and heart failure. Addition of information about NT-proBNP concentration to a model containing conventional risk factors was associated with a C-index increase of 0·012 (0·010-0·014) and a net reclassification improvement of 0·027 (0·019-0·036) for the combination of coronary heart disease and stroke and a C-index increase of 0·019 (0·016-0·022) and a net reclassification improvement of 0·028 (0·019-0·038) for the combination of coronary heart disease, stroke, and heart failure. INTERPRETATION: In people without baseline cardiovascular disease, NT-proBNP concentration assessment strongly predicted first-onset heart failure and augmented coronary heart disease and stroke prediction, suggesting that NT-proBNP concentration assessment could be used to integrate heart failure into cardiovascular disease primary prevention. FUNDING: British Heart Foundation, Austrian Science Fund, UK Medical Research Council, National Institute for Health Research, European Research Council, and European Commission Framework Programme 7.

Best (but oft-forgotten) practices: the design, analysis, and interpretation of Mendelian randomization studies.

Mendelian randomization (MR) is an increasingly important tool for appraising causality in observational epidemiology. The technique exploits the principle that genotypes are not generally susceptible to reverse causation bias and confounding, reflecting their fixed nature and Mendel's first and second laws of inheritance. The approach is, however, subject to important limitations and assumptions that, if unaddressed or compounded by poor study design, can lead to erroneous conclusions. Nevertheless, the advent of 2-sample approaches (in which exposure and outcome are measured in separate samples) and the increasing availability of open-access data from large consortia of genome-wide association studies and population biobanks mean that the approach is likely to become routine practice in evidence synthesis and causal inference research. In this article we provide an overview of the design, analysis, and interpretation of MR studies, with a special emphasis on assumptions and limitations. We also consider different analytic strategies for strengthening causal inference. Although impossible to prove causality with any single approach, MR is a highly cost-effective strategy for prioritizing intervention targets for disease prevention and for strengthening the evidence base for public health policy.

Temporal trends in falls cases seen by EMS in Melbourne: The effect of residence on time of day and day of week patterns.

BACKGROUND: Injury due to falls is a major public health problem, especially for older people. We aimed to determine the accuracy of the ambulance call taker triage algorithm relative to paramedic assessment, and characterise variation in ambulance service demand for falls cases involving older adults over time and by residence type. METHOD: We obtained all ambulance case records for January 2008 to December 2011 for adults aged 65 or over in Melbourne, Australia. Data elements comprised age, gender, date and time of emergency call, dispatch category, location of incident and the patient's clinical condition as ascertained by paramedics. We compared cases coded as falls by the call taker triage algorithm with those identified by paramedics. We also examined temporal variation (hour of day and day of week) in ambulance service demand for cases involving older adults, and compared community-dwelling cases and those from Residential Aged Care Facilities (RACFs). We used negative binomial regression to compare counts and trigonometric regression to compare temporal variation patterns. RESULTS: Over the four-year study period 77,891 falls cases involved older adults (6.5% of overall ambulance demand). Eighty-seven per cent of paramedic-assessed falls cases were correctly identified by the triage system. The RACF population was older (median age 87 years, IQR 82-91 vs. 82 years, IQR 76-87), had higher hospital transport rates (89.5% vs. 75.8%) and a higher incidence of falls at any age than the community-dwelling population. The temporal pattern for fall cases for all residence types peaked between 6:00 and 12:00, but fall cases from RACFs showed an additional peak in the evening between 17:00 and 20:00. CONCLUSION: Falls by older people are the second-biggest contributor to ambulance demand in Melbourne, consuming significant operational resources. Using call taker triage data instead of paramedic case records to calculate falls cases may underestimate the true incidence of falls by up to 13%. Temporal patterns can inform ambulance service policy and practice, falls referral and prevention programmes to optimise service delivery which will lessen the number of future falls cases.

Network Mendelian randomization: using genetic variants as instrumental variables to investigate mediation in causal pathways.

BACKGROUND: Mendelian randomization uses genetic variants, assumed to be instrumental variables for a particular exposure, to estimate the causal effect of that exposure on an outcome. If the instrumental variable criteria are satisfied, the resulting estimator is consistent even in the presence of unmeasured confounding and reverse causation. METHODS: We extend the Mendelian randomization paradigm to investigate more complex networks of relationships between variables, in particular where some of the effect of an exposure on the outcome may operate through an intermediate variable (a mediator). If instrumental variables for the exposure and mediator are available, direct and indirect effects of the exposure on the outcome can be estimated, for example using either a regression-based method or structural equation models. The direction of effect between the exposure and a possible mediator can also be assessed. Methods are illustrated in an applied example considering causal relationships between body mass index, C-reactive protein and uric acid. RESULTS: These estimators are consistent in the presence of unmeasured confounding if, in addition to the instrumental variable assumptions, the effects of both the exposure on the mediator and the mediator on the outcome are homogeneous across individuals and linear without interactions. Nevertheless, a simulation study demonstrates that even considerable heterogeneity in these effects does not lead to bias in the estimates. CONCLUSIONS: These methods can be used to estimate direct and indirect causal effects in a mediation setting, and have potential for the investigation of more complex networks between multiple interrelated exposures and disease outcomes.

Sample size and power calculations in Mendelian randomization with a single instrumental variable and a binary outcome.

BACKGROUND: Sample size calculations are an important tool for planning epidemiological studies. Large sample sizes are often required in Mendelian randomization investigations. METHODS AND RESULTS: Resources are provided for investigators to perform sample size and power calculations for Mendelian randomization with a binary outcome. We initially provide formulae for the continuous outcome case, and then analogous formulae for the binary outcome case. The formulae are valid for a single instrumental variable, which may be a single genetic variant or an allele score comprising multiple variants. Graphs are provided to give the required sample size for 80% power for given values of the causal effect of the risk factor on the outcome and of the squared correlation between the risk factor and instrumental variable. R code and an online calculator tool are made available for calculating the sample size needed for a chosen power level given these parameters, as well as the power given the chosen sample size and these parameters. CONCLUSIONS: The sample size required for a given power of Mendelian randomization investigation depends greatly on the proportion of variance in the risk factor explained by the instrumental variable. The inclusion of multiple variants into an allele score to explain more of the variance in the risk factor will improve power, however care must be taken not to introduce bias by the inclusion of invalid variants.

Judging a patient's decision to seek emergency healthcare: clues for managing increasing patient demand.

OBJECTIVE: In recent years, the concept of an 'inappropriate' emergency department or ambulance user has arisen. This discussion paper explores definition and measurement of inappropriate emergency healthcare utilisation, and the effect on demand. METHOD: A comprehensive literature review of published articles was conducted. RESULTS: Exploration of the definitions of 'inappropriate' emergency healthcare utilisation identified two patient cohorts; emergency healthcare utilisation by those who are not experiencing a health emergency, and those who do not seek emergency healthcare who should. Several position papers from Australian and international sources emphasised the patient's right to access emergency healthcare when they feel the need, and the responsibility of emergency healthcare workers to provide treatment to all patients. Differences between medical classifications of urgency based on physiological measures are contrasted with patient-based determination of urgency, which is defined by psychosocial factors. CONCLUSIONS: This literature review raises questions about patients' understanding of the role of emergency healthcare services in an emergency. This has implications for determining the patient's point of access to the health system in an acute health event, and offers an opportunity to selectively educate patients and carers to change help-seeking behaviours to suit the health system resources and moderate patient demand.

What is a health emergency? The difference in definition and understanding between patients and health professionals.

BACKGROUND: Investigations into 'inappropriate' use of emergency health services are limited by the lack of definition of what constitutes a health emergency. Position papers from Australian and international sources emphasise the patient's right to access emergency healthcare, and the responsibility of emergency health care workers to provide treatment to all patients. However, discordance between the two perspectives remain, with literature labelling patient use of emergency health services as 'inappropriate'. OBJECTIVE: To define a 'health emergency' and compare patient and health professionals perspectives. METHOD: A sample of 600 emergency department (ED) patients were surveyed about a recent health experience and asked to rate their perceived urgency. This rating was compared to their triage score allocated at the hospital ED. RESULTS: No significant relationship was found between the two ratings of urgency (P=0.51). CONCLUSIONS; Differing definitions of a 'health emergency' may explain patient help-seeking behaviour when accessing emergency health resources including hospital ED and ambulance services. A new definition of health emergency that encapsulates the health professional and patient perspectives is proposed. An agreed definition of when emergency health resources should be used has the potential to improve emergency health services demand and patient flow issues, and optimise emergency health resource allocation.